On nonlinearity in neural encoding models applied to the primary visual cortex

Within the regression framework, we show how different levels of nonlinearity influence the instantaneous firing rate prediction of single neurons. Nonlinearity can be achieved in several ways. In particular, we can enrich the predictor set with basis expansions of the input variables (enlarging the number of inputs) or train a simple but different model for each area of the data domain. Spline-based models are popular within the first category. Kernel smoothing methods fall into the second category. Whereas the first choice is useful for globally characterizing complex functions, the second is very handy for temporal data and is able to include inner-state subject variations. Also, interactions among stimuli are considered. We compare state-of-the-art firing rate prediction methods with some more sophisticated spline-based nonlinear methods: multivariate adaptive regression splines and sparse additive models. We also study the impact of kernel smoothing. Finally, we explore the combination of various local models in an incremental learning procedure. Our goal is to demonstrate that appropriate nonlinearity treatment can greatly improve the results. We test our hypothesis on both synthetic data and real neuronal recordings in cat primary visual cortex, giving a plausible explanation of the results from a biological perspective.

Cloud Computing Service for Managing Large Medical Image Data-Sets Using Balanced Collaborative Agents

Managing large medical image collections is an increasingly demanding important issue in many hospitals and other medical settings. A huge amount of this information is daily generated, which requires robust and agile systems. In this paper we present a distributed multi-agent system capable of managing very large medical image datasets. In this approach, agents extract low-level information from images and store them in a data structure implemented in a relational database. The data structure can also store semantic information related to images and particular regions. A distinctive aspect of our work is that a single image can be divided so that the resultant sub-images can be stored and managed separately by different agents to improve performance in data accessing and processing. The system also offers the possibility of applying some region-based operations and filters on images, facilitating image classification. These operations can be performed directly on data structures in the database.

A graph-based approach for latency modeling and optimization in multiview video encoding

We present a novel framework for encoding latency analysis of arbitrary multiview video coding prediction structures. This framework avoids the need to consider an specific encoder architecture for encoding latency analysis by assuming an unlimited processing capacity on the multiview encoder. Under this assumption, only the influence of the prediction structure and the processing times have to be considered, and the encoding latency is solved systematically by means of a graph model. The results obtained with this model are valid for a multiview encoder with sufficient processing capacity and serve as a lower bound otherwise. Furthermore, with the objective of low latency encoder design with low penalty on rate-distortion performance, the graph model allows us to identify the prediction relationships that add higher encoding latency to the encoder. Experimental results for JMVM prediction structures illustrate how low latency prediction structures with a low rate-distortion penalty can be derived in a systematic manner using the new model.

A New Fast Motion Estimation and Mode Decision algorithm for H.264 Depth Maps encoding in Free Viewpoint TV

In this paper, we consider a scenario where 3D scenes are modeled through a View+Depth representation. This representation is to be used at the rendering side to generate synthetic views for free viewpoint video. The encoding of both type of data (view and depth) is carried out using two H.264/AVC encoders. In this scenario we address the reduction of the encoding complexity of depth data. Firstly, an analysis of the Mode Decision and Motion Estimation processes has been conducted for both view and depth sequences, in order to capture the correlation between them. Taking advantage of this correlation, we propose a fast mode decision and motion estimation algorithm for the depth encoding. Results show that the proposed algorithm reduces the computational burden with a negligible loss in terms of quality of the rendered synthetic views. Quality measurements have been conducted using the Video Quality Metric.

Remote Effects of Hippocampal Sclerosis on Effective Connectivity during Working Memory Encoding: A Case of Connectional Diaschisis?

Accumulating evidence suggests a role for the medial temporal lobe (MTL) in working memory (WM). However, little is known concerning its functional interactions with other cortical regions in the distributed neural network subserving WM. To reveal these, we availed of subjects with MTL damage and characterized changes in effective connectivity while subjects engaged in WM task. Specifically, we compared dynamic causal models, extracted from magnetoencephalographic recordings during verbal WM encoding, in temporal lobe epilepsy patients (with left hippocampal sclerosis) and controls. Bayesian model comparison indicated that the best model (across subjects) evidenced bilateral, forward, and backward connections, coupling inferior temporal cortex (ITC), inferior frontal cortex (IFC), and MTL. MTL damage weakened backward connections from left MTL to left ITC, a decrease accompanied by strengthening of (bidirectional) connections between IFC and MTL in the contralesional hemisphere. These findings provide novel evidence concerning functional interactions between nodes of this fundamental cognitive network and sheds light on how these interactions are modified as a result of focal damage to MTL. The findings highlight that a reduced (top-down) influence of the MTL on ipsilateral language regions is accompanied by enhanced reciprocal coupling in the undamaged hemisphere providing a first demonstration of “connectional diaschisis.”

A Balanced Memory-Based Collaborative Filtering Similarity Measure.

Collaborative filtering recommender systems contribute to alleviating the problem of information overload that exists on the Internet as a result of the mass use of Web 2.0 applications. The use of an adequate similarity measure becomes a determining factor in the quality of the prediction and recommendation results of the recommender system, as well as in its performance. In this paper, we present a memory-based collaborative filtering similarity measure that provides extremely high-quality and balanced results; these results are complemented with a low processing time (high performance), similar to the one required to execute traditional similarity metrics. The experiments have been carried out on the MovieLens and Netflix databases, using a representative set of information retrieval quality measures.

Cromosomal location of four genes encoding Class III peroxidases in wheat

In a previous work, deduced amino acid sequences from twenty wheat peroxidase genes were assigned to seven groups designated as TaPrx108 to TaPrx114. Some of these apoplastic peroxidases have previously shown to play different roles in the plant defense responses to infection by the cereal cyst nematode Heterodera avenae. In the present study, PCR marker analysis using Sears’s aneuploid wheat lines cv. ‘Chinese Spring’ was used to locate four genes encoding peroxidase isozymes. The TaPrx111-A, TaPrx112-D and TaPrx113-F genes were located on the short arm of chromosome 2B and the TaPrx109-C on the long arm of chromosome 1B. These results would agree with the synteny between wheat and rice chromosomes previously established in other studies.

New PV self-orientating roof based on a balanced movement

New PV self-orientating roof based on a balanced movement

Brain dynamics of mild cognitive impairment during face encoding

Brain oscillations are closely correlated with human information processing and fundamental aspects of cognition. Previous literature shows that due to the relation between brain oscillations and memory processes, spectral dynamics during such tasks are good candidates to study and characterize memory related pathologies. Mild cognitive impairment (MCI), defined as a clinical condition characterized by memory impairment and/ or deterioration of additional cognitive domains, is considered a preliminary stage in the dementia process. In consequence, the study of its brain patterns could help to achieve an early diagnosis of Alzheimer Disease.

Balanced scorecard to improve strategic management control at School of Mines and Energy, Universidad Politécnica de Madrid

We studied the situation in Spanish public universities regarding the use of the Balanced Scorecard (BSC), as an instrument of control and strategic management. Also, we studied its application to the School of Mines and Energy at Universidad Politécnica de Madrid. The main advantage of the BSC is that improves the organizational structure of the workplace and the achievement of the objectives that ensure long-term success. First we review the strategy for success used in the Spanish educational system and specifically in the Spanish public universities. Then using the BSC and applying the main strategic lines for the successful management of the School of Mines and Energy at Universidad Politécnica de Madrid. The strategic lines affect all the college groups and the success of the BSC tool is to increase communication between the faculties, personal auxiliary, students and society in general that make up the university. First we performed a SWOT analysis (DAFO in Spanish) there are proposed different perspectives that focus the long-term strategic objectives. The BSC is designed based on the strategic objectives that set the direction through using indicators and initiatives, the goals are achieved up to the programmed schedule. In the perspective of teaching, objectives are set to update facilities and increase partnerships with other universities and businesses, encouraging ongoing training of staff and improved coordination and internal communication. The internal process perspective aims at improving the marketing, the promotion of the international dimension of the school through strategic alliances, better mobility for students and professors and improved teaching and research quality results. It continues with improving the image of the school between customer?s perspective, the quality perceived by students and the loyalty of the teaching staff by retaining talent. Finally, the financial perspective which should contain costs without harming the quality, improving the employability of students and achieve relevant jobs at teaching and research through international measurement standards.

The AtCathB3 gene, encoding a cathepsin B-like protease, is expressed during germination of Arabidopsis thaliana and transcriptionally repressed by the basic leucine zipper protein GBF1.

Protein hydrolysis plays an important role during seed germination and post-germination seedling establishment. In Arabidopsis thaliana, cathepsin B-like proteases are encoded by a gene family of three members, but only the AtCathB3 gene is highly induced upon seed germination and at the early post-germination stage. Seeds of a homozygous T-DNA insertion mutant in the AtCathB3 gene have, besides a reduced cathepsin B activity, a slower germination than the wild type. To explore the transcriptional regulation of this gene, we used a combined phylogenetic shadowing approach together with a yeast one-hybrid screening of an arrayed library of approximately 1200 transcription factor open reading frames from Arabidopsis thaliana. We identified a conserved CathB3-element in the promoters of orthologous CathB3 genes within the Brassicaceae species analysed, and, as its DNA-interacting protein, the G-Box Binding Factor1 (GBF1). Transient overexpression of GBF1 together with a PAtCathB3::uidA (β-glucuronidase) construct in tobacco plants revealed a negative effect of GBF1 on expression driven by the AtCathB3 promoter. In stable P35S::GBF1 lines, not only was the expression of the AtCathB3 gene drastically reduced, but a significant slower germination was also observed. In the homozygous knockout mutant for the GBF1 gene, the opposite effect was found. These data indicate that GBF1 is a transcriptional repressor of the AtCathB3 gene and affects the germination kinetics of Arabidopsis thaliana seeds. As AtCathB3 is also expressed during post-germination in the cotyledons, a role for the AtCathB3-like protease in reserve mobilization is also inferred.

Arabidopsis thaliana bZIP44: a transcription factor affecting seed germination and expression of the mannanase-encoding gene AtMAN7.

Endo-β-mannanases (MAN; EC. 3.2.1.78) catalyze the cleavage of β1[RIGHTWARDS ARROW]4 bonds in mannan polymers and have been associated with the process of weakening the tissues surrounding the embryo during seed germination. In germinating Arabidopsis thaliana seeds, the most highly expressed MAN gene is AtMAN7 and its transcripts are restricted to the micropylar endosperm and to the radicle tip just before radicle emergence. Mutants with a T-DNA insertion in AtMAN7 have a slower germination than the wild type. To gain insight into the transcriptional regulation of the AtMAN7 gene, a bioinformatic search for conserved non-coding cis-elements (phylogenetic shadowing) within the Brassicaceae MAN7 gene promoters has been done, and these conserved motifs have been used as bait to look for their interacting transcription factors (TFs), using as a prey an arrayed yeast library from A. thaliana. The basic-leucine zipper TF AtbZIP44, but not the closely related AtbZIP11, has thus been identified and its transcriptional activation upon AtMAN7 has been validated at the molecular level. In the knock-out lines of AtbZIP44, not only is the expression of the AtMAN7 gene drastically reduced, but these mutants have a significantly slower germination than the wild type, being affected in the two phases of the germination process, both in the rupture of the seed coat and in the breakage of the micropylar endosperm cell walls. In the over-expression lines the opposite phenotype is observed.

Sophisticated security verification on routing repaired balanced cell-based dual-rail logic against side channel analysis

Conventional dual-rail precharge logic suffers from difficult implementations of dual-rail structure for obtaining strict compensation between the counterpart rails. As a light-weight and high-speed dual-rail style, balanced cell-based dual-rail logic (BCDL) uses synchronised compound gates with global precharge signal to provide high resistance against differential power or electromagnetic analyses. BCDL can be realised from generic field programmable gate array (FPGA) design flows with constraints. However, routings still exist as concerns because of the deficient flexibility on routing control, which unfavourably results in bias between complementary nets in security-sensitive parts. In this article, based on a routing repair technique, novel verifications towards routing effect are presented. An 8 bit simplified advanced encryption processing (AES)-co-processor is executed that is constructed on block random access memory (RAM)-based BCDL in Xilinx Virtex-5 FPGAs. Since imbalanced routing are major defects in BCDL, the authors can rule out other influences and fairly quantify the security variants. A series of asymptotic correlation electromagnetic (EM) analyses are launched towards a group of circuits with consecutive routing schemes to be able to verify routing impact on side channel analyses. After repairing the non-identical routings, Mutual information analyses are executed to further validate the concrete security increase obtained from identical routing pairs in BCDL.

Nitrogen fixation by native Bradyrhizobia in symbiosis with Lupinus mariae-josephae requires a T3SS encoding a NopE-like effector

Several bradyrhizobial isolates from L. mariae-josephae root nodules [1] contain a type III secretion system (T3SS) within a cluster of about 30 genes. Among those genes, ttsI codes for the transcriptional activator of the system. Mutation of ttsI resulted in the formation of white, non-fixing nodules with the natural legume host, L. mariae-josephae. The T3SS cluster also contains a gene coding for a NopE-like protein. NopE proteins have been demonstrated to be effectors in the Bradyrhizobium-soybean symbiosis [2] and belong to a small group of poorly characterized proteins from plant-associated bacteria that contain one or two autocleavage motifs known as DUF1521 (Schirrmeister et al. 2011). The amino acid sequence of a NopE-like protein in the L. mariae-josephae strain LmjC contains just one autocatalytic motif. This is unlike NopE1 and NopE2 proteins secreted by the T3SS of B. japonicum, that contain two motifs [3]. The autocleavage of LmjC NopE protein was analyzed after expression in E. coli and purification. Two protein fragments of the predicted sizes appeared in the presence of Ca2+, Cu2+, Cd2+, Zn2+ and Mn2+ cations. In contrast, autocleavage did not take place in the presence of Ni2+, Co2+ or Mg2+. Site-directed mutagenesis of the DUF1521 motif in LmjC NopE abolished self-cleavage in vitro. Symbiotic competence of a NopE- mutant with the L. mariae-josephae host was not affected. Possible roles of NopE are discussed.

A framework for the analysis and optimization of encoding latency for multiview video

We present a novel framework for the analysis and optimization of encoding latency for multiview video. Firstly, we characterize the elements that have an influence in the encoding latency performance: (i) the multiview prediction structure and (ii) the hardware encoder model. Then, we provide algorithms to find the encoding latency of any arbitrary multiview prediction structure. The proposed framework relies on the directed acyclic graph encoder latency (DAGEL) model, which provides an abstraction of the processing capacity of the encoder by considering an unbounded number of processors. Using graph theoretic algorithms, the DAGEL model allows us to compute the encoding latency of a given prediction structure, and determine the contribution of the prediction dependencies to it. As an example of DAGEL application, we propose an algorithm to reduce the encoding latency of a given multiview prediction structure up to a target value. In our approach, a minimum number of frame dependencies are pruned, until the latency target value is achieved, thus minimizing the degradation of the rate-distortion performance due to the removal of the prediction dependencies. Finally, we analyze the latency performance of the DAGEL derived prediction structures in multiview encoders with limited processing capacity.